Multi-omics analysis of primary glioblastoma cell lines shows recapitulation of pivotal molecular features of parental tumors

Neuro-Oncology

Volumn 19, Issue 2, 2017, Pages 219-228

  Rosenberg, Shai ^a,d   Verreault, Maïté ^a   Schmitt, Charlotte ^a   Guegan, Justine ^b   Guehennec, Jeremy ^a   Levasseur, Camille ^a   Marie, Yannick ^a,b   Bielle, Franck ^a,c   Mokhtari, Karima ^a,c   Hoang Xuan, Khê ^a,c   Ligon, Keith ^e   Sanson, Marc ^a,c   Delattre, Jean Yves ^a,c   Idbaih, Ahmed ^a,c  

^a SORBONNE UNIVERSITÉ   (France)

^b INSTITUT DU CERVEAU ET DE LA MOELLE ÉPINIÈRE   (France)

^c PITIÉ SALPÊTRIÈRE HOSPITAL   (France)

^d HADASSAH HEBREW UNIVERSITY MEDICAL CENTER   (Israel)

^e DANA FARBER CANCER INSTITUTE   (United States)

Author keywords

Cancer; Cell lines; Genome; Glioblastoma

Indexed keywords

ANIMAL MODEL; BIOLOGY; CANCER GROWTH; CLINICAL ARTICLE; COPY NUMBER VARIATION; DRIVER; FEMALE; GENE EXPRESSION PROFILING; GENE OVEREXPRESSION; GLIOBLASTOMA CELL LINE; HUMAN; HUMAN CELL; LANDSCAPE; MALE; POINT MUTATION; PRECLINICAL STUDY; RNA SEQUENCE; SINGLE NUCLEOTIDE POLYMORPHISM; TUMOR MODEL; WHOLE EXOME SEQUENCING; AGED; BRAIN TUMOR; EXOME; GENETICS; GLIOBLASTOMA; HIGH THROUGHPUT SEQUENCING; MIDDLE AGED; PATHOLOGY; PROCEDURES; REAL TIME POLYMERASE CHAIN REACTION; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; TUMOR CELL CULTURE;

MESSENGER RNA; TUMOR MARKER;

AGED; BIOMARKERS, TUMOR; BRAIN NEOPLASMS; DNA COPY NUMBER VARIATIONS; EXOME; FEMALE; GENE EXPRESSION PROFILING; GLIOBLASTOMA; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MALE; MIDDLE AGED; POINT MUTATION; POLYMORPHISM, SINGLE NUCLEOTIDE; REAL-TIME POLYMERASE CHAIN REACTION; REVERSE TRANSCRIPTASE POLYMERASE CHAIN REACTION; RNA, MESSENGER; TUMOR CELLS, CULTURED;

EID: 85019721017     PISSN: 15228517     EISSN: 15235866     Source Type: Journal    
DOI: 10.1093/neuonc/now160     Document Type: Article

References (31)

1. Prados MD, Byron SA, Tran NL, et al. Toward precision medicine in glioblastoma: the promise and the challenges. Neuro Oncol. 2015;17(8):1051-1063.
2. Kwak EL, Bang Y-J, Camidge DR, et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N Engl J Med. 2010;363(18):1693-1703.
3. Ciardiello F, Tortora G. EGFR antagonists in cancer treatment. N Engl J Med. 2008;358(11):1160-1174.
4. Ciriello G, Miller ML, Aksoy BA, et al. Emerging landscape of oncogenic signatures across human cancers. Nat Genet. 2013;45(10):1127-1133.
5. Lazar V, Rubin E, Depil S, et al. A simplified interventional mapping system (SIMS) for the selection of combinations of targeted treatments in non-small cell lung cancer. Oncotarget. 2015;6(16):14139-14152.
6. Barretina J, Caponigro G, Stransky N, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483(7391):603-607.
7. Li A, Liu Z, Lezon-Geyda K, et al. GPHMM: an integrated hidden Markov model for identification of copy number alteration and loss of heterozygosity in complex tumor samples using whole genome SNP arrays. Nucleic Acids Res. 2011;39(12):4928-4941.
8. DePristo MA, Banks E, Poplin R, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43(5):491-498.
9. Cibulskis K, Lawrence MS, Carter SL, et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol. 2013;31(3):213-219.
10. Ramos AH, Lichtenstein L, Gupta M, et al. Oncotator: cancer variant annotation tool. Hum. Mutat. 2015;36(4):E2423-E2429.
11. Gonzalez-Perez A, Perez-Llamas C, Deu-Pons J, et al. IntOGenmutations identifies cancer drivers across tumor types. Nat Methods. 2013;10(11):1081-1082.
12. Forbes SA, Beare D, Gunasekaran P, et al. COSMIC: exploring the world's knowledge of somatic mutations in human cancer. Nucleic Acids Res. 2015;43(Database issue):D805-811.
13. Brennan CW, Verhaak RG, McKenna A, et al. The somatic genomic landscape of glioblastoma. Cell. 2013;155(2):462-477.
14. My Cancer Genome 2013. http://www.mycancergenome.org. Accessed May 21, 2015.
15. Ritchie ME, Phipson B, Wu D, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43(7):e47.
16. Verhaak RGW, Hoadley KA, Purdom E, et al. Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1. Cancer Cell. 2010;17(1):98-110.
17. Reich M, Liefeld T, Gould J, et al. GenePattern 2.0. Nat Genet. 2006;38(5):500-501.
18. IPA, Qiagen Redwood City. www.qiagen. com/ingenuity. Accessed February 2, 2016.
19. Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(43):15545-15550.
20. Liberzon A. A description of the Molecular Signatures Database (MSigDB) Web site. Methods Mol. Biol. 2014;1150:153-160.
21. Carter SL, Cibulskis K, Helman E, et al. Absolute quantification of somatic DNA alterations in human cancer. Nat Biotechnol. 2012;30(5):413-421.
22. Olshen AB, Venkatraman ES, Lucito R, et al. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics. 2004;5(4):557-572.
23. Joseph JV, Balasubramaniyan V, Walenkamp A, et al. TGF-beta as a therapeutic target in high grade gliomas - promises and challenges. Biocheml Pharmacol. 2013;85(4):478-485.
24. TCGA Fusion Gene Data Portal. 54.84.12.177/PanCanFusV2/. Accessed December 5, 2015.
25. Domcke S, Sinha R, Levine DA, et al. Evaluating cell lines as tumour models by comparison of genomic profiles. Nat Commun. 2013;4:2126.
26. Lee J, Kotliarova S, Kotliarov Y, et al. Tumor stem cells derived from glioblastomas cultured in bFGF and EGF more closely mirror the phenotype and genotype of primary tumors than do serum-cultured cell lines. Cancer Cell. 2006;9(5):391-403.
27. Davis B, Shen Y, Poon CC, et al. Comparative genomic and genetic analysis of glioblastoma-derived brain tumor-initiating cells and their parent tumors. Neuro Oncol. 2015.
28. Orr BA, Eberhart CG. Nature versus nurture in glioblastoma: microenvironment and genetics can both drive mesenchymal transcriptional signature. Am J Pathol. 2012;180(5):1768-1771.
29. Sottoriva A, Spiteri I, Piccirillo SG, et al. Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics. Proc Natl Acad Sci U S A. 2013;110(10):4009-4014.
30. Xie Y, Bergstrom T, Jiang Y, et al. The Human Glioblastoma Cell Culture Resource: Validated Cell Models Representing All Molecular Subtypes. EBio Medicine. 2015;2(10):1351-1363.
31. Alizadeh AA, Aranda V, Bardelli A, et al. Toward understanding and exploiting tumor heterogeneity. Nat Med. 2015;21(8):846-853.